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xusenlinzy / api-for-open-llm

Openai style api for open large language models, using LLMs just as chatgpt! Support for LLaMA, LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, Xverse, SqlCoder, CodeLLaMA, ChatGLM, ChatGLM2, ChatGLM3 etc. 开源大模型的统一后端接口
Apache License 2.0
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Using llama.cpp engine 能正常启动，但是对话出现 500错误 #199

Closed Fbai700 closed 6 months ago

Fbai700 commented 6 months ago

提交前必须检查以下项目 | The following items must be checked before submission

问题类型 | Type of problem

模型推理和部署 | Model inference and deployment

操作系统 | Operating system

Windows

详细描述问题 | Detailed description of the problem

加载正常，但是无法，对话

Dependencies

仅使用 pip install -r requirements.txt 进行依赖安装

运行日志或截图 | Runtime logs or screenshots

2023-12-12 14:14:37.638 | DEBUG | api.config::250 - SETTINGS: { "host": "0.0.0.0", "port": 8000, "api_prefix": "/v1", "engine": "llama.cpp", "model_name": "baichuan2", "model_path": "F:\models\llm\baichuan2-7b-chat.Q3_K_L.gguf", "adapter_model_path": null, "resize_embeddings": false, "dtype": "half", "device": "cuda", "device_map": null, "gpus": null, "num_gpus": 1, "only_embedding": false, "embedding_name": null, "embedding_size": -1, "embedding_device": "cuda", "quantize": 16, "load_in_8bit": false, "load_in_4bit": false, "using_ptuning_v2": false, "pre_seq_len": 128, "context_length": -1, "chat_template": null, "patch_type": null, "alpha": "auto", "trust_remote_code": false, "tokenize_mode": "auto", "tensor_parallel_size": 1, "gpu_memory_utilization": 0.9, "max_num_batched_tokens": -1, "max_num_seqs": 256, "quantization_method": null, "use_streamer_v2": false, "api_keys": null, "activate_inference": true, "interrupt_requests": true, "n_gpu_layers": -1, "main_gpu": 0, "tensor_split": null, "n_batch": 512, "n_threads": 6, "n_threads_batch": 6, "rope_scaling_type": -1, "rope_freq_base": 0.0, "rope_freq_scale": 0.0, "tgi_endpoint": null } llama_model_loader: loaded meta data with 19 key-value pairs and 291 tensors from F:\models\llm\baichuan2-7b-chat.Q3_K_L.gguf (version GGUF V2) llama_model_loader: - tensor 0: token_embd.weight q3_K [ 4096, 125696, 1, 1 ] llama_model_loader: - tensor 1: blk.0.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 2: blk.0.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 3: blk.0.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 4: blk.0.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 5: blk.0.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 6: blk.0.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 7: blk.1.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 8: blk.1.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 9: blk.1.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 10: blk.1.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 11: blk.1.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 12: blk.1.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 13: blk.2.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 14: blk.2.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 15: blk.2.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 16: blk.2.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 17: blk.2.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 18: blk.2.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 19: blk.3.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 20: blk.3.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 21: blk.3.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 22: blk.3.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 23: blk.3.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 24: blk.3.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 25: blk.4.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 26: blk.4.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 27: blk.4.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 28: blk.4.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 29: blk.4.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 30: blk.4.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 31: blk.5.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 32: blk.5.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 33: blk.5.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 34: blk.5.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 35: blk.5.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 36: blk.5.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 37: blk.6.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 38: blk.6.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 39: blk.6.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 40: blk.6.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 41: blk.6.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 42: blk.6.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 43: blk.7.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 44: blk.7.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 45: blk.7.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 46: blk.7.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 47: blk.7.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 48: blk.7.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 49: blk.8.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 50: blk.8.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 51: blk.8.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 52: blk.8.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 53: blk.8.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 54: blk.8.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 55: blk.9.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 56: blk.9.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 57: blk.9.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 58: blk.9.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 59: blk.9.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 60: blk.9.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 61: blk.10.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 62: blk.10.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 63: blk.10.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 64: blk.10.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 65: blk.10.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 66: blk.10.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 67: blk.11.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 68: blk.11.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 69: blk.11.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 70: blk.11.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 71: blk.11.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 72: blk.11.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 73: blk.12.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 74: blk.12.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 75: blk.12.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 76: blk.12.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 77: blk.12.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 78: blk.12.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 79: blk.13.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 80: blk.13.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 81: blk.13.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 82: blk.13.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 83: blk.13.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 84: blk.13.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 85: blk.14.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 86: blk.14.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 87: blk.14.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 88: blk.14.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 89: blk.14.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 90: blk.14.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 91: blk.15.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 92: blk.15.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 93: blk.15.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 94: blk.15.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 95: blk.15.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 96: blk.15.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 97: blk.16.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 98: blk.16.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 99: blk.16.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 100: blk.16.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 101: blk.16.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 102: blk.16.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 103: blk.17.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 104: blk.17.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 105: blk.17.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 106: blk.17.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 107: blk.17.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 108: blk.17.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 109: blk.18.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 110: blk.18.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 111: blk.18.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 112: blk.18.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 113: blk.18.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 114: blk.18.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 115: blk.19.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 116: blk.19.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 117: blk.19.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 118: blk.19.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 119: blk.19.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 120: blk.19.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 121: blk.20.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 122: blk.20.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 123: blk.20.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 124: blk.20.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 125: blk.20.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 126: blk.20.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 127: blk.21.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 128: blk.21.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 129: blk.21.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 130: blk.21.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 131: blk.21.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 132: blk.21.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 133: blk.22.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 134: blk.22.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 135: blk.22.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 136: blk.22.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 137: blk.22.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 138: blk.22.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 139: blk.23.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 140: blk.23.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 141: blk.23.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 142: blk.23.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 143: blk.23.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 144: blk.23.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 145: blk.24.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 146: blk.24.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 147: blk.24.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 148: blk.24.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 149: blk.24.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 150: blk.24.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 151: blk.25.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 152: blk.25.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 153: blk.25.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 154: blk.25.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 155: blk.25.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 156: blk.25.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 157: blk.26.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 158: blk.26.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 159: blk.26.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 160: blk.26.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 161: blk.26.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 162: blk.26.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 163: blk.27.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 164: blk.27.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 165: blk.27.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 166: blk.27.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 167: blk.27.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 168: blk.27.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 169: blk.28.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 170: blk.28.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 171: blk.28.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 172: blk.28.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 173: blk.28.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 174: blk.28.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 175: blk.29.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 176: blk.29.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 177: blk.29.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 178: blk.29.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 179: blk.29.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 180: blk.29.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 181: blk.30.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 182: blk.30.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 183: blk.30.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 184: blk.30.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 185: blk.30.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 186: blk.30.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 187: blk.31.attn_output.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 188: blk.31.ffn_gate.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 189: blk.31.ffn_down.weight q5_K [ 11008, 4096, 1, 1 ] llama_model_loader: - tensor 190: blk.31.ffn_up.weight q3_K [ 4096, 11008, 1, 1 ] llama_model_loader: - tensor 191: blk.31.attn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 192: blk.31.ffn_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 193: output_norm.weight f32 [ 4096, 1, 1, 1 ] llama_model_loader: - tensor 194: output.weight q6_K [ 4096, 125696, 1, 1 ] llama_model_loader: - 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tensor 247: blk.17.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 248: blk.17.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 249: blk.18.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 250: blk.18.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 251: blk.18.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 252: blk.19.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 253: blk.19.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 254: blk.19.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 255: blk.20.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 256: blk.20.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 257: blk.20.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 258: blk.21.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 259: blk.21.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 260: blk.21.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 261: blk.22.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 262: blk.22.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 263: blk.22.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 264: blk.23.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 265: blk.23.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 266: blk.23.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 267: blk.24.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 268: blk.24.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 269: blk.24.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 270: blk.25.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 271: blk.25.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 272: blk.25.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 273: blk.26.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 274: blk.26.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 275: blk.26.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 276: blk.27.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 277: blk.27.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 278: blk.27.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 279: blk.28.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 280: blk.28.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 281: blk.28.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 282: blk.29.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 283: blk.29.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 284: blk.29.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 285: blk.30.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 286: blk.30.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 287: blk.30.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 288: blk.31.attn_q.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 289: blk.31.attn_k.weight q3_K [ 4096, 4096, 1, 1 ] llama_model_loader: - tensor 290: blk.31.attn_v.weight q5_K [ 4096, 4096, 1, 1 ] llama_model_loader: - kv 0: general.architecture str = llama llama_model_loader: - kv 1: general.name str = LLaMA v2 llama_model_loader: - kv 2: llama.context_length u32 = 4096 llama_model_loader: - kv 3: llama.embedding_length u32 = 4096 llama_model_loader: - kv 4: llama.block_count u32 = 32 llama_model_loader: - kv 5: llama.feed_forward_length u32 = 11008 llama_model_loader: - kv 6: llama.rope.dimension_count u32 = 128 llama_model_loader: - kv 7: llama.attention.head_count u32 = 32 llama_model_loader: - kv 8: llama.attention.head_count_kv u32 = 32 llama_model_loader: - kv 9: llama.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 10: general.file_type u32 = 13 llama_model_loader: - kv 11: tokenizer.ggml.model str = llama llama_model_loader: - kv 12: tokenizer.ggml.tokens arr[str,125696] = ["", "", "", "", "<C... llama_model_loader: - kv 13: tokenizer.ggml.scores arr[f32,125696] = [0.000000, 0.000000, 0.000000, 0.0000... llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,125696] = [2, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 15: tokenizer.ggml.bos_token_id u32 = 1 llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 2 llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 18: general.quantization_version u32 = 2 llama_model_loader: - type f32: 65 tensors llama_model_loader: - type q3_K: 129 tensors llama_model_loader: - type q5_K: 96 tensors llama_model_loader: - type q6_K: 1 tensors llm_load_vocab: mismatch in special tokens definition ( 1298/125696 vs 259/125696 ). llm_load_print_meta: format = GGUF V2 llm_load_print_meta: arch = llama llm_load_print_meta: vocab type = SPM llm_load_print_meta: n_vocab = 125696 llm_load_print_meta: n_merges = 0 llm_load_print_meta: n_ctx_train = 4096 llm_load_print_meta: n_embd = 4096 llm_load_print_meta: n_head = 32 llm_load_print_meta: n_head_kv = 32 llm_load_print_meta: n_layer = 32 llm_load_print_meta: n_rot = 128 llm_load_print_meta: n_gqa = 1 llm_load_print_meta: f_norm_eps = 0.0e+00 llm_load_print_meta: f_norm_rms_eps = 1.0e-06 llm_load_print_meta: f_clamp_kqv = 0.0e+00 llm_load_print_meta: f_max_alibi_bias = 0.0e+00 llm_load_print_meta: n_ff = 11008 llm_load_print_meta: rope scaling = linear llm_load_print_meta: freq_base_train = 10000.0 llm_load_print_meta: freq_scale_train = 1 llm_load_print_meta: n_yarn_orig_ctx = 4096 llm_load_print_meta: rope_finetuned = unknown llm_load_print_meta: model type = 7B llm_load_print_meta: model ftype = mostly Q3_K - Large llm_load_print_meta: model params = 7.51 B llm_load_print_meta: model size = 3.80 GiB (4.34 BPW) llm_load_print_meta: general.name = LLaMA v2 llm_load_print_meta: BOS token = 1 '' llm_load_print_meta: EOS token = 2 '' llm_load_print_meta: UNK token = 0 '' llm_load_print_meta: PAD token = 0 '' llm_load_print_meta: LF token = 1099 '<0x0A>' llm_load_tensors: ggml ctx size = 0.11 MiB llm_load_tensors: mem required = 3887.37 MiB ....................................................................................... llama_new_context_with_model: n_ctx = 2048 llama_new_context_with_model: freq_base = 10000.0 llama_new_context_with_model: freq_scale = 1 llama_new_context_with_model: kv self size = 1024.00 MiB llama_build_graph: non-view tensors processed: 740/740 llama_new_context_with_model: compute buffer total size = 256.56 MiB AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 0 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 | 2023-12-12 14:14:39.276 | INFO | api.models:create_llama_cpp_engine:129 - Using llama.cpp engine INFO: Started server process [3464] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit) 2023-12-12 14:15:09.808 | INFO | api.llama_cpp_routes.chat:create_chat_completion:28 - Received chat messages: [{'content': "Please answer the user's questions in Chinese! 请用中文回答用户提出的问题！！！", 'role': 'system'}, {'content': '霓虹', 'role': 'user'}] INFO: 127.0.0.1:60733 - "POST /v1/chat/completions HTTP/1.1" 500 Internal Server Error ERROR: Exception in ASGI application Traceback (most recent call last): File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\uvicorn\protocols\http\httptools_impl.py", line 426, in run_asgi result = await app( # type: ignore[func-returns-value] File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\uvicorn\middleware\proxy_headers.py", line 84, in call return await self.app(scope, receive, send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\fastapi\applications.py", line 1106, in call await super().call(scope, receive, send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\applications.py", line 122, in call await self.middleware_stack(scope, receive, send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\middleware\errors.py", line 184, in call raise exc File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\middleware\errors.py", line 162, in call await self.app(scope, receive, _send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\middleware\cors.py", line 83, in call await self.app(scope, receive, send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\middleware\exceptions.py", line 79, in call raise exc File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\middleware\exceptions.py", line 68, in call await self.app(scope, receive, sender) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\fastapi\middleware\asyncexitstack.py", line 20, in call raise e File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\fastapi\middleware\asyncexitstack.py", line 17, in call await self.app(scope, receive, send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\routing.py", line 718, in call await route.handle(scope, receive, send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\routing.py", line 276, in handle await self.app(scope, receive, send) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\starlette\routing.py", line 66, in app response = await func(request) File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\fastapi\routing.py", line 274, in app raw_response = await run_endpoint_function( File "F:\llmcode\train\LLaMA-Factory\env\lib\site-packages\fastapi\routing.py", line 191, in run_endpoint_function return await dependant.call(**values) File "F:\llmcode\api\api-for-open-llm\api\llama_cpp_routes\chat.py", line 33, in create_chat_completion request, stop_token_ids = await handle_request(request, engine.stop) ValueError: too many values to unpack (expected 2)

xusenlinzy commented 6 months ago

已经修复了，更新一下代码试试